Open AccessBlood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus
Author(s) -
Crecil Dias Cifha,
Kamath Surekha,
Vidyasagar Sudha
Publication year - 2020
Publication title -
iet systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.367
H-Index - 50
eISSN - 1751-8857
pISSN - 1751-8849
DOI - 10.1049/iet-syb.2019.0101
Subject(s) - setpoint , artificial pancreas , glucagon , model predictive control , insulin , diabetes mellitus , medicine , controller (irrigation) , endocrinology , control theory (sociology) , type 1 diabetes , hypoglycemia , blood sugar regulation , tracking error , predictive value , computer science , control (management) , biology , artificial intelligence , agronomy
This study elaborates on the design of artificial pancreas using model predictive control algorithm for a comprehensive physiological model such as the Sorensen model, which regulates the blood glucose and can have a longer control time in normal glycaemic region. The main objective of the proposed algorithm is to eliminate the risk of hyper and hypoglycaemia and have a precise infusion of hormones: insulin and glucagon. A single model predictive controller is developed to control the bihormones, insulin, and glucagon for such a development unmeasured disturbance is considered for a random time. The simulation result for the proposed algorithm performed good regulation lowering the hypoglycaemia risk and maintaining the glucose level within the normal glycaemic range. To validate the performance of the tracking of output and setpoint, average tracking error is used and 4.4 mg/dl results are obtained while compared with standard value (14.3 mg/dl).